Transparent and flexible photonic artificial synapse with piezo-phototronic modulator: Versatile memory capability and higher order learning algorithm
- 1. Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012 (Korea, Republic of)
- 2. Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012 (Korea, Republic of)
- 3. School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332 (United States)
Description
Highlights: • Highly transparent and flexible two-terminal photonic artificial synapse. • The device shows purely photo-triggered all essential synaptic functions. • All synaptic functions were modulated in multi-levels by input signals. • Learning algorithm is performed by using photonic pulses. -- Abstract: An artificial photonic synapse having tunable manifold synaptic response can be an essential step forward for the advancement of novel neuromorphic computing. In this work, we reported the development of highly transparent and flexible two-terminal ZnO/Ag-nanowires/PET photonic artificial synapse. The device shows purely photo-triggered all essential synaptic functions such as transition from short-to long-term plasticity, paired-pulse facilitation, and spike-timing-dependent plasticity, including in the versatile memory capability. Importantly, strain-induced piezo-phototronic effect within ZnO provides an additional degree of regulation to modulate all of the synaptic functions in multi-levels. The observed effect is quantitatively explained as a dynamic of photo-induced electron-hole trapping/detraining via the defect states such as oxygen vacancies. We revealed that the synaptic functions can be consolidated and converted by applied strain, which is not previously applied any of the reported synaptic devices. This study will open a new avenue to the scientific community to control and design highly transparent wearable neuromorphic computing.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.nanoen.2019.06.039Additional details
Identifiers
- DOI
- 10.1016/j.nanoen.2019.06.039;
- PII
- S2211285519305439;
Publishing Information
- Journal Title
- Nano Energy (Print)
- Journal Volume
- 63
- Journal Page Range
- vp.
- ISSN
- 2211-2855
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 54114940
- Subject category
- S77: NANOSCIENCE AND NANOTECHNOLOGY;
- Descriptors DEI
- ALGORITHMS; DESIGN; ELECTRONS; NANOWIRES; OXYGEN; PLASTICITY; PULSES; SIGNALS; VACANCIES; ZINC OXIDES
- Descriptors DEC
- CHALCOGENIDES; CRYSTAL DEFECTS; CRYSTAL STRUCTURE; ELEMENTARY PARTICLES; ELEMENTS; FERMIONS; LEPTONS; MATHEMATICAL LOGIC; MECHANICAL PROPERTIES; NANOSTRUCTURES; NONMETALS; OXIDES; OXYGEN COMPOUNDS; POINT DEFECTS; ZINC COMPOUNDS
Optional Information
- Copyright
- Copyright (c) 2019 Elsevier Ltd. All rights reserved.